Software Tools for Earth and Environmental Science
– 10th WEEK –
Emir Toker
14/11/2019
R Promgramming - Part 2
- Syllabus and Book
- DataCamp Class
- Practice - R Language
- Practice - R Programming
Coffee Break
- R Programming - repeat Loops
- R Programming - while Loops
- R Programming - for Loops
- R Programming - apply Loops
QUIZ
- Next Week
Syllabus, Book
Syllabus
Book
Homework-1 and Midterm Project
?
DataCamp Class
DataCamp Class
DataCamp Class
(1$ = 5,75 TL)
29$ * 5,75 TL * 6 Months * 1 Student= 833,75 TL
833,75 TL * 25 Students = 20.843,75 TL
Practice - R Language
Practice - R Language
Objectives
Manage Working Directory
Find the Data
Read Data with utils (R utility functions)
Practice - R Language
Manage Working Directory
- getwd() - get working directory
- list.files() # or dir()
getwd()## [1] "/Users/emirtoker/Desktop/Dersler/Memurluk/Software_Tools_for_Earth_&_Environmental_Science/Software_Tools_R_Github/Presentation"list.files()## [1] "18397_Cekmekoy_Omerli_15dk.txt"
## [2] "18397_Cekmekoy_Omerli.csv"
## [3] "18397_Cekmekoy_Omerli.xlsx"
## [4] "agu_pre.png"
## [5] "ai.png"
## [6] "algorithm.png"
## [7] "alma.jpg"
## [8] "anaconda.png"
## [9] "analysis.png"
## [10] "apache_point.jpg"
## [11] "apply_1.png"
## [12] "arcgis.png"
## [13] "arit_op.png"
## [14] "array.png"
## [15] "ascii_1.png"
## [16] "ascii_2.png"
## [17] "aybe_seminar.png"
## [18] "big_data1.png"
## [19] "book_7th.png"
## [20] "book_chp1.png"
## [21] "book_cover_week5.png"
## [22] "book_cover_week9.png"
## [23] "book_flow.png"
## [24] "book_week5.png"
## [25] "cd1.png"
## [26] "cd2.png"
## [27] "cdo.png"
## [28] "cdo1.png"
## [29] "cdo2.png"
## [30] "cdo3.png"
## [31] "cdo4.png"
## [32] "cdo5.png"
## [33] "clear.png"
## [34] "code.png"
## [35] "coercion_mini.png"
## [36] "coercion.png"
## [37] "command_line.png"
## [38] "concept_array_q.png"
## [39] "concept_array.png"
## [40] "conda.png"
## [41] "conditions_book.png"
## [42] "course_github.png"
## [43] "coursera.png"
## [44] "cp.png"
## [45] "cp1.png"
## [46] "cran_metu.png"
## [47] "cran_turkey.png"
## [48] "cru.png"
## [49] "cygwin.png"
## [50] "data_analytics.png"
## [51] "data_assim.jpeg"
## [52] "data_frame.png"
## [53] "data_mining.svg"
## [54] "data_structure_copy.png"
## [55] "data_structure.png"
## [56] "data_structure1_array.png"
## [57] "data_structure1_copy.png"
## [58] "data_structure1.png"
## [59] "data_types.png"
## [60] "data.csv"
## [61] "datacamp.png"
## [62] "datacamp1.png"
## [63] "datascience.png"
## [64] "datashape.jpg"
## [65] "datum.png"
## [66] "dc1.png"
## [67] "dc10.png"
## [68] "dc11.png"
## [69] "dc2.png"
## [70] "dc3.png"
## [71] "dc4.png"
## [72] "dc5.png"
## [73] "dc5a.png"
## [74] "dc5aa.png"
## [75] "dc5ab.png"
## [76] "dc5ac.png"
## [77] "dc6.png"
## [78] "dc7.png"
## [79] "dc8.png"
## [80] "dc9.png"
## [81] "deep.jpg"
## [82] "dene_sill_files"
## [83] "dene_sill.html"
## [84] "dene_sill.Rmd"
## [85] "denemepdf.docx"
## [86] "denemepdf.html"
## [87] "denemepdf.nb.html"
## [88] "denemepdf.pdf"
## [89] "dffile.csv"
## [90] "dffile.txt"
## [91] "download.png"
## [92] "dropbox.png"
## [93] "dt10w.png"
## [94] "earthdata.png"
## [95] "eda.png"
## [96] "edx.png"
## [97] "ensemble.png"
## [98] "eobs.png"
## [99] "era.png"
## [100] "esgf.png"
## [101] "excel.png"
## [102] "exit.png"
## [103] "extended_4th_week.png"
## [104] "extended_syllabus_3th_week.png"
## [105] "extended_syllabus.png"
## [106] "extended_syllabus1.png"
## [107] "fig_temp.png"
## [108] "fig.html"
## [109] "fig.png"
## [110] "filer_folder.png"
## [111] "filezil.png"
## [112] "filezilla.png"
## [113] "find.png"
## [114] "forecast.png"
## [115] "generate.png"
## [116] "gfs.png"
## [117] "github.png"
## [118] "github1.png"
## [119] "github2.png"
## [120] "github3.png"
## [121] "github4.png"
## [122] "gnu_logo_small.png"
## [123] "gnu_logo.png"
## [124] "grib_1.png"
## [125] "grib.jpg"
## [126] "grid_diff.jpg"
## [127] "grid_sample.jpg"
## [128] "gridded.jpg"
## [129] "hdf5_structure.jpg"
## [130] "help.png"
## [131] "history.png"
## [132] "if1.png"
## [133] "if1a.png"
## [134] "if1b.png"
## [135] "if1c.png"
## [136] "if2.png"
## [137] "if2a.png"
## [138] "if3.png"
## [139] "if3a.png"
## [140] "if3b.png"
## [141] "if3c.png"
## [142] "if3d.png"
## [143] "integral_fig.png"
## [144] "integral_fig1.png"
## [145] "iot.png"
## [146] "july_pre.png"
## [147] "jupyter_notebook.png"
## [148] "jupyter.png"
## [149] "kernel.jpg"
## [150] "khanacademy.png"
## [151] "knmi.png"
## [152] "languages.png"
## [153] "lapply2.png"
## [154] "last_week_2nd.png"
## [155] "last_week.png"
## [156] "linus.jpeg"
## [157] "linux_dist.png"
## [158] "linux_logo.png"
## [159] "list_1.jpg"
## [160] "list0.png"
## [161] "list2.png"
## [162] "logic_op.png"
## [163] "machine.jpg"
## [164] "mat1.jpg"
## [165] "mat1.png"
## [166] "matrice_cut.png"
## [167] "matrices.png"
## [168] "matrices1.png"
## [169] "mendeley.png"
## [170] "metadata0.png"
## [171] "metadata1.png"
## [172] "meted.png"
## [173] "MidTerm_Project_Emir.html"
## [174] "MidTerm_Project_Emir.pdf"
## [175] "MidTerm_Project_Emir.Rmd"
## [176] "MidTerm_Project.html"
## [177] "MidTerm_Project.pdf"
## [178] "MidTerm_Project.Rmd"
## [179] "mining.jpg"
## [180] "mining1.jpg"
## [181] "mkdir1.png"
## [182] "mkdir2.png"
## [183] "model.png"
## [184] "mv.png"
## [185] "my_notebook.png"
## [186] "my_profile"
## [187] "my_r_notebook_1.png"
## [188] "my_r_notebook_html.png"
## [189] "my_r_notebook_pdf.png"
## [190] "my_r_notebook_word.png"
## [191] "my_r_notebook.png"
## [192] "my_r_team_invite.pdf"
## [193] "my_r_team_invite.png"
## [194] "mynewfile.png"
## [195] "nc.png"
## [196] "ncl.png"
## [197] "ncl0.png"
## [198] "ncl1.png"
## [199] "ncl2.png"
## [200] "ncll.png"
## [201] "nco_diff.png"
## [202] "nco.png"
## [203] "ncview.png"
## [204] "netcdf_1.png"
## [205] "netcdf.png"
## [206] "new_data.csv"
## [207] "nwp_1.png"
## [208] "nwp_2.png"
## [209] "observation_data.png"
## [210] "orcid.png"
## [211] "os.png"
## [212] "overleaf.png"
## [213] "page_7th.png"
## [214] "page_week5.png"
## [215] "panoply.png"
## [216] "Pdf_Week5_-_R_Language_Part_1_files"
## [217] "Pdf_Week5_-_R_Language_Part_1.pdf"
## [218] "Pdf_Week5_-_R_Language_Part_1.Rmd"
## [219] "practice_1_w5.png"
## [220] "practice_func.png"
## [221] "Presentation_Week1_-_Data_and_Code.html"
## [222] "Presentation_Week1_-_Data_and_Code.Rmd"
## [223] "Presentation_Week10_-_R_Programming_Part_2.html"
## [224] "Presentation_Week10_-_R_Programming_Part_2.Rmd"
## [225] "Presentation_Week2_-_Linux_and_Python.html"
## [226] "Presentation_Week2_-_Linux_and_Python.pdf"
## [227] "Presentation_Week2_-_Linux_and_Python.Rmd"
## [228] "Presentation_Week3_-_Data_Sources_and_Download.html"
## [229] "Presentation_Week3_-_Data_Sources_and_Download.Rmd"
## [230] "Presentation_Week4_-_Introduction_to_R.html"
## [231] "Presentation_Week4_-_Introduction_to_R.Rmd"
## [232] "Presentation_Week5_-_R_Language_Part_1.html"
## [233] "Presentation_Week5_-_R_Language_Part_1.Rmd"
## [234] "Presentation_Week7_-_R_Language_Part_3.html"
## [235] "Presentation_Week7_-_R_Language_Part_3.Rmd"
## [236] "Presentation_Week9_-_R_Programming_Part_1_files"
## [237] "Presentation_Week9_-_R_Programming_Part_1.html"
## [238] "Presentation_Week9_-_R_Programming_Part_1.Rmd"
## [239] "Presentation.Rproj"
## [240] "printenv.png"
## [241] "pwd_mac.png"
## [242] "pwd_mac1.png"
## [243] "pwd_win.png"
## [244] "python_term.png"
## [245] "python.jpg"
## [246] "qgis.png"
## [247] "R_and_R_Studio.jpeg"
## [248] "R_and_R_Studio.png"
## [249] "r_book_week5.png"
## [250] "r_classic1.png"
## [251] "r_classic2.png"
## [252] "r_clust.jpg"
## [253] "r_comp.png"
## [254] "r_corr.png"
## [255] "r_dplyr.png"
## [256] "r_files.png"
## [257] "r_inter.png"
## [258] "r_linear.png"
## [259] "R_logo.jpeg"
## [260] "r_markdown.png"
## [261] "r_screen1.png"
## [262] "r_screen10.png"
## [263] "r_screen11.png"
## [264] "r_screen12.png"
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## [267] "r_screen15.png"
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## [269] "r_screen17.png"
## [270] "r_screen18.png"
## [271] "r_screen19.png"
## [272] "r_screen2.png"
## [273] "r_screen20.png"
## [274] "r_screen21.png"
## [275] "r_screen22.png"
## [276] "r_screen23.png"
## [277] "r_screen24.png"
## [278] "r_screen25.png"
## [279] "r_screen3.png"
## [280] "r_screen4.png"
## [281] "r_screen5.png"
## [282] "r_screen6.png"
## [283] "r_screen7.png"
## [284] "r_screen8.png"
## [285] "r_screen9.png"
## [286] "r_script_w5.png"
## [287] "r_shiny.png"
## [288] "r_shiny1.png"
## [289] "r_storms.gif"
## [290] "r_team_members.pdf"
## [291] "r_team_members.png"
## [292] "r_team_pending.pdf"
## [293] "r_team_pending.png"
## [294] "r_terminal.png"
## [295] "r_time.gif"
## [296] "r_visual.png"
## [297] "r_web.png"
## [298] "r-for-loop.png"
## [299] "r-for1.png"
## [300] "r-for2.png"
## [301] "r-loops.png"
## [302] "r-repeat-loop.png"
## [303] "r-while-loop.png"
## [304] "raster_0.gif"
## [305] "raster_dataset.png"
## [306] "raster_vs_vector.png"
## [307] "rcsv.png"
## [308] "rdelim.png"
## [309] "reanalysis.jpg"
## [310] "researchgate.png"
## [311] "Richard.jpg"
## [312] "rid1.png"
## [313] "rid2.png"
## [314] "rid3.png"
## [315] "rid4.png"
## [316] "rm.png"
## [317] "robert_gentleman.jpg"
## [318] "root_fig.gif"
## [319] "root.png"
## [320] "ross_lhaka.jpg"
## [321] "Rplot.png"
## [322] "rsconnect"
## [323] "rstudio_cloud.png"
## [324] "rstudio_down.png"
## [325] "rstudio_logo.png"
## [326] "rstudio_product.png"
## [327] "rstudio_ubuntu.png"
## [328] "rstudio.png"
## [329] "rtb1.png"
## [330] "rtb2.png"
## [331] "sci_math.png"
## [332] "shp_mask.png"
## [333] "shp.png"
## [334] "sil_notebook_files"
## [335] "sil_notebook.html"
## [336] "sil_notebook.nb.html"
## [337] "sil_notebook.Rmd"
## [338] "sil_rmarkdown_files"
## [339] "sil_rmarkdown.html"
## [340] "sil_rmarkdown.Rmd"
## [341] "sil_sweave-concordance.tex"
## [342] "sil_sweave.log"
## [343] "sil_sweave.Rnw"
## [344] "sil_sweave.tex"
## [345] "simulation.jpg"
## [346] "Software_Tools_R_Homework2.html"
## [347] "Software_Tools_R_Homework2.nb.html"
## [348] "Software_Tools_R_Homework2.pdf"
## [349] "Software_Tools_R_Homework2.Rmd"
## [350] "Software_Tools_R_Homework3_Answer.nb.html"
## [351] "Software_Tools_R_Homework3_Answer.Rmd"
## [352] "Software_Tools_R_Homework3.nb.html"
## [353] "Software_Tools_R_Homework3.pdf"
## [354] "Software_Tools_R_Homework3.Rmd"
## [355] "somenewfile.txt"
## [356] "stackoverflow.png"
## [357] "sublimetext.png"
## [358] "syllabus_4th_week.png"
## [359] "syllabus_5th.png"
## [360] "syllabus_7th.png"
## [361] "syllabus_9.png"
## [362] "syllabus_w6.png"
## [363] "syllabus_week5.png"
## [364] "syllabus.png"
## [365] "syllabus7_son.png"
## [366] "teamviewer.png"
## [367] "terminal.png"
## [368] "terminal0.png"
## [369] "terminal1.png"
## [370] "th_1.gif"
## [371] "th_1.png"
## [372] "th_2.gif"
## [373] "th_2.jpg"
## [374] "th_3.gif"
## [375] "The_Book_of_R_small.png"
## [376] "The_Book_of_R.png"
## [377] "touch.png"
## [378] "udemy_content_1.png"
## [379] "udemy_hm1.png"
## [380] "udemy.png"
## [381] "udemy1.png"
## [382] "unix_develop.jpg"
## [383] "unix_linux.png"
## [384] "VAPOR_HAIL_ANIME.gif"
## [385] "vec_rep.png"
## [386] "vector_type_1.jpg"
## [387] "vector_type.png"
## [388] "vector_vs_raster.png"
## [389] "vector.png"
## [390] "vector1a.png"
## [391] "vector1b.png"
## [392] "vi_0.png"
## [393] "vi_1.png"
## [394] "vi_2.png"
## [395] "vi_3.png"
## [396] "visual.jpg"
## [397] "warning.png"
## [398] "webminal.png"
## [399] "week-book.png"
## [400] "Week1_rpubs.html"
## [401] "Week1_rpubs.Rmd"
## [402] "week10_book.png"
## [403] "week10.html"
## [404] "week10.png"
## [405] "week10.Rmd"
## [406] "week100.png"
## [407] "week2_sil.html"
## [408] "week2_sil.log"
## [409] "week2_sil.Rmd"
## [410] "week2_sil.tex"
## [411] "week3.html"
## [412] "week3.Rmd"
## [413] "week4_extended_syllabus.png"
## [414] "week4.html"
## [415] "week4.Rmd"
## [416] "week5.html"
## [417] "week5.Rmd"
## [418] "week7.html"
## [419] "week7.Rmd"
## [420] "week9.html"
## [421] "week9.Rmd"
## [422] "weight_height.txt"
## [423] "wetransfer.png"
## [424] "wget.jpg"
## [425] "what_data.svg"
## [426] "win_folder.png"
## [427] "wolfram-alpha.png"
## [428] "wordclim.png"
## [429] "zenodo-doi.png"Practice - R Language
Manage Working Directory
- setwd() - set working directory
# 1
setwd("/Users/emirtoker/Downloads/")
# 2
getwd()## [1] "/Users/emirtoker/Downloads"list.files()## [1] "-3597101405606164018..xls"
## [2] "-this_is_my_file.csv"
## [3] "[Barry_Saltzman_(Eds.)]_Dynamical_Paleoclimatology(z-lib.org).pdf"
## [4] "[Chjan_Lim,_Joseph_Nebus]_Vorticity,_statistical_m(z-lib.org).pdf"
## [5] "[Christian,_Ph.d_Soize]_Stochastic_models_of_uncer(z-lib.org).pdf"
## [6] "[Cyril_Fleurant,_Sandrine_Bodin-Fleurant]_Mathemat(z-lib.org).pdf"
## [7] "[David_Atlas_(eds.)]_Radar_in_Meteorology__Battan_(z-lib.org).pdf"
## [8] "[David_J._Stensrud]_Parameterization_Schemes__Keys(z-lib.org).pdf"
## [9] "[Geoffrey_K._Vallis]_Atmospheric_and_Oceanic_Fluid(z-lib.org).pdf"
## [10] "[Gerold_Siedler,_Stephen_M._Griffies,_John_Gould_a(b-ok.cc).pdf"
## [11] "[Joseph_Pedlosky]_Geophysical_Fluid_Dynamics(z-lib.org).pdf"
## [12] "[Paul_Teetor]_R_Cookbook_(O'Reilly_Cookbooks)(z-lib.org).pdf"
## [13] "[Petty,_Grant_William]_A_first_course_in_atmospher(z-lib.org).pdf"
## [14] "[Raymond_S._Bradley]_Paleoclimatology_-_Reconstruc(z-lib.org).pdf"
## [15] "[Thomas_M._Cronin]_Principles_of_Paleoclimatology(z-lib.org).pdf"
## [16] "[Vivien_Gornitz]_Encyclopedia_of_Paleoclimatology_(z-lib.org).pdf"
## [17] "[Xiao-Sheng_Si,_Zheng-Xin_Zhang,_Chang-Hua_Hu_(aut(z-lib.org).pdf"
## [18] "~$UBYT_2019_Yılı_Dergi-_Listesi.xlsx"
## [19] "0002-1571(71)90039-2.pdf"
## [20] "0034-4885_14_1_306.pdf"
## [21] "02786829808965531.pdf"
## [22] "1_aybe_arazi_aracı_talep_dilekçesi.docx"
## [23] "1_Proje+Basvurusu+Rehberi.pdf"
## [24] "1-s2-0-s092181811830688-x-main-2.pdf"
## [25] "1-s2.0-S0169809512001214-main.pdf"
## [26] "1-s2.0-S0169809517312553-main.pdf"
## [27] "1-s2.0-S2214581816303482-main.pdf"
## [28] "10.3906-sag-1206-68-126599.pdf.crdownload"
## [29] "100_2000_basvuru_formu_3.docx"
## [30] "101101.ppt"
## [31] "114854.pdf"
## [32] "12-website"
## [33] "12-website.zip"
## [34] "12.2204891.pdf"
## [35] "1520-0469(1958)015_0044_AOSCSO_2.0.CO;2.pdf"
## [36] "18397_Cekmekoy_Omerli (1).csv"
## [37] "18397_Cekmekoy_Omerli.csv"
## [38] "19394386126 (1).pdf"
## [39] "19394386126.pdf"
## [40] "1977_Book_HailAReviewOfHailScienceAndHai (1).pdf"
## [41] "1977_Book_HailAReviewOfHailScienceAndHai.pdf"
## [42] "2008_Famiglietti_WRR (1).pdf"
## [43] "2008_Famiglietti_WRR (2).pdf"
## [44] "2008_Famiglietti_WRR.pdf"
## [45] "2018_BEC_BIN_SM_A_20181031T013358_20181101T000814_NOMINAL_025_003.nc"
## [46] "2018_BEC_BIN_SM_A_20181208T001426_20181209T002848_NOMINAL_025_003.nc"
## [47] "2018-2019-lisanakademik-ayrintilix_636701153862396694.xlsx"
## [48] "2019_danışman-değişikliği-dilekçesi.docx"
## [49] "2019_eş-danışman-atama-dilekçesi.docx"
## [50] "211928 (1).zip"
## [51] "211928.nrg"
## [52] "211928.nrg 2"
## [53] "211928.zip"
## [54] "2170-Article Text-13012-1-10-20181113.pdf"
## [55] "26-10-2019-tarihli-ogretim-uyesi-ilani.pdf"
## [56] "279_L1C_TB_ATBD_RevA_web.pdf"
## [57] "2798828.pdf"
## [58] "31.doc"
## [59] "3Bolum.doc"
## [60] "4462549.acsm"
## [61] "52719179_855167214825657_5575230819250545040_n.mp4"
## [62] "601181009-47926-2019-11-02-22-25-51 (1).pdf"
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## [455] "signature.htm"
## [456] "signature.txt"
## [457] "Simla-Tez Şablonu(29.10.2019).docx"
## [458] "Simla-Tez Şablonu(6.10.2019).docx"
## [459] "simpreg.xls"
## [460] "SimulatingHeavyPrecipitation_HARMONIE_HIRLAM_WRF.pdf"
## [461] "Skewt_d04.ncl.txt"
## [462] "Skjern_shapeFILES"
## [463] "Skjern_shapeFILES.zip"
## [464] "SM_data.zip"
## [465] "SMAP_L2_SM_SP_1AIWDV_20181011T004447_20181010T001623_086E38N_R16010_001.h5.iso.xml"
## [466] "SMAP_L3_FT_P_E_20150401_R16010_001.h5.iso.xml"
## [467] "smos.zip"
## [468] "SN_d_tot_V2.0.csv"
## [469] "SN_d_tot_V2.0.txt"
## [470] "socat_search_result_url_list_20181209-160829.txt"
## [471] "Software_Installation_Manual (1).pdf"
## [472] "Software_Installation_Manual (2).pdf"
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## [480] "Spatial Correlation new (1).doc"
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## [482] "Spatial Correlation new.doc"
## [483] "subversion-1.12.2"
## [484] "subversion-1.12.2.tar.bz2"
## [485] "surucu-belgesi-gerekli-belgeler.pdf"
## [486] "SwTaurus_2019.mp4"
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## [491] "Tao.ppt"
## [492] "Taşıt Görev Emri Formu (1).doc"
## [493] "Taşıt Görev Emri Formu.doc"
## [494] "temel-isgb.pptx"
## [495] "Termius.dmg"
## [496] "tgrs.1990.572906.pdf"
## [497] "The_Mediterranean_Valleys.bibtex"
## [498] "ThesisJanbertAarnink.pdf"
## [499] "Time_Series.ncl (1).txt"
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## [520] "Vaisala IRIS Focus 2.1 Admin Guide.pdf"
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## [563] "ZIP_MSG_SEVIRI_SPEC_RES_CHAR.zip"file.path("~","Users","emirtoker","Downloads","-this_is_my_file.csv")## [1] "~/Users/emirtoker/Downloads/-this_is_my_file.csv"Practice - R Language
Find the Data
- file.path()
# Option 1
# setwd("/Users/emirtoker/Downloads/")
# read.csv("-this_is_my_file.csv")
# Option 2
path <- file.path("~","Users","emirtoker","Downloads","-this_is_my_file.csv")
path## [1] "~/Users/emirtoker/Downloads/-this_is_my_file.csv"# read.csv(path)Practice - R Language
Read Data
with utils (R utility functions)
- read.csv() - Comma Seperated Value
- read.delim() - Tab Delimited Data
- read.table() - Exocit file format
Practice - R Language
Read Data with utils (R utility functions)
read.csv() - Comma Seperated Value
Practice - R Language
Read Data with utils (R utility functions)
read.delim() - Tab Delimited Data
Practice - R Language
Read Data with utils (R utility functions)
read.table() - Exocit file format
Practice - R Language
BONUS - Import Dataset
Practice - R Language
BONUS - Import Dataset
Practice - R Language
BONUS - Import Dataset
Practice - R Language
BONUS - Import Dataset
Practice - R Language
BONUS - Import Dataset
17061_Sariyer_Sariyer_15dk<- read.csv( “~/Desktop/NCL_Script_ve_Gorsel/Makale/ time_series_makale/mgm_veri/17061_Sariyer_Sariyer_15dk.txt”, header=FALSE, sep=“;”)View(
17061_Sariyer_Sariyer_15dk)
~
Practice - R Language
Manage Directory, Find and Read Data
Instructions
- Go to main webpage of course
- Open Data “Istanbul_Goztepe_Precipitation_1846-2013_Monthly” (.dat) LINK
- Copy and Paste it in your “Downloads” directory in a text file
- Open your R Studio
We Have 4 Ways to Read
Practice - R Language
Manage Directory, Find and Read Data
Instructions - WAY 1 - GO TO FILE
- Check your Project Name and your Working directory
- Go to “Downloads” directory in R Studio
- List files and Read Data with three different read functions
- read.csv()
- read.delim()
- read.table()
- Choose the best
- Assign your data as “precip_1”
Caraful about header, seperater and missing data
look at the main web page for examples
Practice - R Language
Manage Directory, Find and Read Data
Instructions - WAY 2 - CALL THE FILE
- Go Back to your Working directory
- Define your file path with file.path()
- Assign the path a new variable as “path_my_file”
- Use your best read() function
- Read the file with “path_my_file”
- Assign your data as “precip_2”
path_my_file <- file.path("~","Downloads")
precip_2 <- read.table(path_my_file)Practice - R Language
Manage Directory, Find and Read Data
Instructions - WAY 3 - IMPORT THE FILE
- Use “Import Datase”
- Assign your data as “precip_3”
Practice - R Language
Manage Directory, Find and Read Data
Instructions - WAY 4 - DOWNLOAD THE FILE
- Copy the LINK of data
- Use your best read() function
- Read the file with this function and LINK
- Assign your data as “precip_4”
precip_4 <- read.table("link")Practice - R Programming
Practice - R Programming
Objectives
Identify the Data
Indexing
Use Condition Statements
Plot
Practice - R Programming
Meet with the Data
- Look at structure
- Learn attributes and dimensions
- Rename attributes
? dimensions, variables and types ?
month.name
month.abb
attributes(precip_2)
attributes(precip_2)[1]
attributes(precip_2)[[1]]
attributes(precip_2)[[1]] <- c("Year",month.abb)
attr(precip_2,"names") <- c("Year",month.abb)
attr(precip_2,"row.names") <- 1846:2013
precip_2a <- precip_2[-1]
head(precip_2a)Practice - R Programming
Clear NA and Choose Colomn
- Print “precip_2a”
- Delete rows which include NA ( na.omit() )
- Assign it as “precip_2b”
- Select summer season
- Assign it as “precip_2b_summer”
precip_2b <- na.omit(precip_2a)
precip_2b_summer <- precip_2b[ ,6:8]Practice - R Programming
Use Condition Statements - if
- Compare June Mean Precipitation with July
- IF June mean precipitation is LOWER than July then print “June has low precipitation.”
mean_jun <- mean(precip_2b_summer$Jun)
mean_jul <- mean(precip_2b_summer$Jul)
if (mean_jun > mean_jul) {
print("June has low precipitation.")
}
colMeans(precip_2b_summer)
Practice - R Programming
Use Condition Statements - else
- IF June mean precipitation is LOWER than July then print “June has low precipitation.”
- ELSE print “June has high precipitation.”
- Calculate mean of each month ( colMeans() )
mean_jun <- mean(precip_2b_summer$Jun)
mean_jul <- mean(precip_2b_summer$Jul)
if (mean_jun < mean_jul) {
print("June has low precipitation.")
} else {
print("June has high precipitation.")
}
colMeans(precip_2b_summer)Practice - R Programming
Plot
Problem : Extremes and Outliers
- Plot precipitation for June
- Add title and unit
plot(precip_2b_summer$Jun,
xlab = "Years",
ylab = "Precipitation [mm/month]",
main = "Istanbul Monthly Precipitation - June",
type = "l",
col="blue")Practice - R Programming
Plot
Problem : Extremes and Outliers
- Edit x-axis, which years are they ?
- What about August ?
attr(precip_2b_summer,"row.names")
x_years <- attr(precip_2b_summer,"row.names")
plot(x_years,
precip_2b_summer$Jun,
xlab = "Years",
ylab = "Precipitation [mm/month]",
main = "Istanbul Monthly Precipitation - June",
type = "l",
col="blue")
plot(precip_2b_summer$Aug)Practice - R Programming
Plot
Problem : Extremes and Outliers
Homework-2
Coffee Break
R Programming - Loops
R Programming - Loops
Loops are R’s method for repeating a task, which makes them a useful tool for programming simulations.
R Programming - repeat Loops
R Programming - repeat Loops
repeat
{
message("Happy Groundhog Day!")
break
}R Programming - repeat Loops
coins <- 3
game <- 0
repeat
{
game <- game + 1
coins <- coins -1
print(game)
print("nice try, play again")
if (coins==0) {
break
}
}## [1] 1
## [1] "nice try, play again"
## [1] 2
## [1] "nice try, play again"
## [1] 3
## [1] "nice try, play again"[1] 1
[1] "nice try, play again"
[1] 2
[1] "nice try, play again"
[1] 3
[1] "nice try, play again"R Programming - while Loops
R Programming - while Loops
While loops are like backward repeat loops.
while(condition) {
conditional statement
}R Programming - while Loops
coins <- 3
game <- 0
while(coins >= 0)
{
coins <- coins -1
game <- game + 1
print(game)
print("nice try, play again")
}## [1] 1
## [1] "nice try, play again"
## [1] 2
## [1] "nice try, play again"
## [1] 3
## [1] "nice try, play again"
## [1] 4
## [1] "nice try, play again"R Programming - for Loops
R Programming - for Loops
The third type of loop is to be used when you know exactly how many times you want the code to repeat.
R Programming - for Loops
for(i in 1:2) {
message("just say it ", i, " times")
}## just say it 1 times## just say it 2 timesR Programming - for Loops
for(i in c(1,2) ) {
message("just say it ", i, " times")
}## just say it 1 times## just say it 2 timesfor(i in c("apple","banana") ) {
message("just say it ", i, " times")
}## just say it apple times## just say it banana timesit is related with length of vector
R Programming - for Loops
month.name## [1] "January" "February" "March" "April" "May"
## [6] "June" "July" "August" "September" "October"
## [11] "November" "December"for(month in month.name) {
message("The month of ", month)
}## The month of January## The month of February## The month of March## The month of April## The month of May## The month of June## The month of July## The month of August## The month of September## The month of October## The month of November## The month of DecemberR Programming - apply Loops
R Programming - apply Loops
- The apply() functions form the basis of more complex combinations and helps to perform operations with very few lines of code.
- More specifically, the family is made up of the apply(), lapply() , sapply(), vapply(), mapply(), rapply(), and tapply() functions.
apply(X, MARGIN, FUN, ...)
# X is an array or a matrix, dim(X) must have a positive length
# MARGIN=1, it applies over rows, whereas with
# MARGIN=2, it works over columns. Note that when you use the construct
# MARGIN=c(1,2), it applies to both rows and columns
# FUN, which is the function that you want to apply to the data. apply(precip_2b_summer, MARGIN=1, mean)
apply(precip_2b_summer, MARGIN=2, mean)
apply(precip_2b_summer, MARGIN=c(1,2), mean)
apply(precip_2b_summer, MARGIN=c(2,1), mean)R Programming - apply Loops
R Programming - lapply Loops
lapply(precip_2b_summer,"[",1)
sapply(precip_2b_summer,"[",1)QUIZ
QUIZ
Next Week
Next Week
- QUIZ - Seriously
- Homework - 2 (read and plot)
- Homework - 3 (if, for, function)
DataCamp Assignments
Elementery Statistics